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- Title
Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.
- Authors
Jing Yang; Hailin Wang; Chen Geng; Yakang Dai; Jiansong Ji; Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong
- Abstract
Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.
- Subjects
PULMONARY nodules; LUNG cancer; MACHINE learning; CANCER diagnosis; ARTIFICIAL intelligence in medicine
- Publication
BioMedical Engineering OnLine, 2018, Vol 17, p1
- ISSN
1475-925X
- Publication type
journal article
- DOI
10.1186/s12938-018-0435-2